Riti P. Nanda, Debasmita Bisoi, Abhimanyu Behera, B. Panigrahi, Arpan K. Satapathy
{"title":"基于人工神经网络的风电系统故障分类","authors":"Riti P. Nanda, Debasmita Bisoi, Abhimanyu Behera, B. Panigrahi, Arpan K. Satapathy","doi":"10.1109/ICCMC.2019.8819675","DOIUrl":null,"url":null,"abstract":"The transmission lines are used to supply electrical power from source to load and distribution network is used to distribute the transmitted power among the load. During the distribution of electrical power, different types of conductors, insulators, circuit breakers and relays are used for the protection. Demand for electrical power is increasing day by day. So to increase electrical power generation, different types of Distribute generators are used like solar, wind, tidal, etc. In this work, the wind farm is connected to the grid via long transmission networks. As the complexity increases, probability of fault occurrence increases, which will hamper the consumer service. Concern to the consumer satisfaction, faults should be cleared first. The detection technique should be accurate and intelligent so that it can clear the fault. Artificial neural network technique is an intelligent tool which can clear the fault. In this work, classification of fault is done using ANN in the model. Modeling is done in MATLAB and SIMULINK. The voltage signal is extracted and was given to the ANN as input. The voltage signal is trained and tested with accuracy.","PeriodicalId":232624,"journal":{"name":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Classification of Faults in a Wind Connected Power System Using Artificial Neural Network\",\"authors\":\"Riti P. Nanda, Debasmita Bisoi, Abhimanyu Behera, B. Panigrahi, Arpan K. Satapathy\",\"doi\":\"10.1109/ICCMC.2019.8819675\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The transmission lines are used to supply electrical power from source to load and distribution network is used to distribute the transmitted power among the load. During the distribution of electrical power, different types of conductors, insulators, circuit breakers and relays are used for the protection. Demand for electrical power is increasing day by day. So to increase electrical power generation, different types of Distribute generators are used like solar, wind, tidal, etc. In this work, the wind farm is connected to the grid via long transmission networks. As the complexity increases, probability of fault occurrence increases, which will hamper the consumer service. Concern to the consumer satisfaction, faults should be cleared first. The detection technique should be accurate and intelligent so that it can clear the fault. Artificial neural network technique is an intelligent tool which can clear the fault. In this work, classification of fault is done using ANN in the model. Modeling is done in MATLAB and SIMULINK. The voltage signal is extracted and was given to the ANN as input. The voltage signal is trained and tested with accuracy.\",\"PeriodicalId\":232624,\"journal\":{\"name\":\"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)\",\"volume\":\"154 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCMC.2019.8819675\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 3rd International Conference on Computing Methodologies and Communication (ICCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMC.2019.8819675","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of Faults in a Wind Connected Power System Using Artificial Neural Network
The transmission lines are used to supply electrical power from source to load and distribution network is used to distribute the transmitted power among the load. During the distribution of electrical power, different types of conductors, insulators, circuit breakers and relays are used for the protection. Demand for electrical power is increasing day by day. So to increase electrical power generation, different types of Distribute generators are used like solar, wind, tidal, etc. In this work, the wind farm is connected to the grid via long transmission networks. As the complexity increases, probability of fault occurrence increases, which will hamper the consumer service. Concern to the consumer satisfaction, faults should be cleared first. The detection technique should be accurate and intelligent so that it can clear the fault. Artificial neural network technique is an intelligent tool which can clear the fault. In this work, classification of fault is done using ANN in the model. Modeling is done in MATLAB and SIMULINK. The voltage signal is extracted and was given to the ANN as input. The voltage signal is trained and tested with accuracy.